Jakub Kopal

McGill University | McGill · Department of Biomedical Engineering

Recurrent copy number variations (CNVs) are rare genomic deletions and duplications that can exert profoundly effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have p...

Motor disability is a dominant and restricting symptom in multiple sclerosis, yet its neuroimaging correlates are not fully understood. We apply statistical and machine learning techniques on multimodal neuroimaging data to discriminate between multiple sclerosis patients and healthy controls and to predict motor disability scores in the patients....

Modern neuroscience is seeing burgeoning population data resources: large-scale datasets with thousands of participant profiles of gene expression, brain scanning, and anthropomorphic measures. The depth of phenotyping puts us in a better position than ever to fully embrace major sources of population diversity – traditionally rarely captured in sm...

Naturalistic neuroscience opened the door to new insights into neural circuits that serve real-world dynamic perception. Such studies have often neglected the rich texture of the movie narrative itself, but semantic content can be used to contextualize the induced neural responses. Here, we translated natural language processing tools from machine...

We need analyses capturing major sources of population diversity

Our understanding of epilepsy mechanisms has shifted its focus towards a dynamic, whole-brain network perspective. Several factors, such as circadian and multi-day cycles, are assumed to influence the likelihood of seizure occurrence. Moreover, this seizure susceptibility is critically dependent on anti-epileptic drug dosage. In this study, we aim...

We picture the brain as a complex network of structurally connected regions that are functionally coupled. Brain functions arise from the coordinated activity of distant cortical regions. Connectivity is used to represent the cooperation of segregated and functionally specialized brain regions. Whether it is the analysis of anatomical links, statis...

Recognition memory is the ability to recognize previously encountered events, objects, or people. It is characterized by its robustness and rapidness. Even this relatively simple ability requires the coordinated activity of a surprisingly large number of brain regions. These spatially distributed, but functionally linked regions are interconnected...

Functional connectivity analysis of resting‐state fMRI data has recently become one of the most common approaches to characterizing individual brain function. It has been widely suggested that the functional connectivity matrix is a useful approximate representation of the brain's connectivity, potentially providing behaviorally or clinically relev...

Functional connectivity analysis of resting state fMRI data has recently become one of the most common approaches to characterizing individual brain function. It has been widely suggested that the functional connectivity matrix is a useful approximate representation of the brain's connectivity, potentially providing behaviorally or clinically relev...

Analysis of brain activities in language perception for individuals with different musical backgrounds can be based upon the study of multichannel electroencephalograhy (EEG) signals acquired in different external conditions. The present paper is devoted to the study of the relationship of mental processes and the perception of external stimuli rel...

Recent precision functional mapping of individual human brains has shown that individual brain organization is qualitatively different from group average estimates and that individuals exhibit distinct brain network topologies. How this variability affects the connectivity within individual resting-state networks remains an open question. This is p...

Five mimic muscles were tested by voluntary contraction. Data was recorded by high definition face tracking mode of Kinect 2. Corresponding virtual markers on both sides of the face was identified during neutral facial expression by affine transformation. The proportions of trajectories of markers on the affected and unaffected side of the face ind...

Background and Objective. Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recognize neuropathic changes. This study validates the possibility of extending...

The paper is devoted to the study of facial region temperature changes using a simple thermal imaging camera and to the comparison of their time evolution with the pectoral area motion recorded by the MS Kinect depth sensor. The goal of this research is to propose the use of videorecords as alternative diagnostics of breathing disorders allowing th...

The dynamic structure of the EEG signal is characterized by segments of synchronization and desynchronization. In this paper, the frequency and duration of these segments were monitored during calm meditation and insight meditation in experienced and naive meditators. A newly developed methodology based on complex continuous wavelet coherence was u...

Recognition memory principally involves the medial temporal lobes, most notably the perirhinal cortex and than the hippocampus. The rhinal cortex is activated earlier than the hippocampus, suggesting it should be involved in the earliest behavioural responses. However, this has never been demonstrated. We used intracerebral recordings in epileptic...

Complex continuous wavelet coherence (WTC) can be used for non-stationary signals, such as electroencephalograms. Areas of the WTC with a coherence higher than the calculated optimal threshold were obtained, and the sum of their areas was used as a criterion to differentiate between groups of experienced insight-focused meditators, calm-focused med...

In this study, the performance of Sevcik’s algorithm that calculates the fractal dimension and permutation entropy as discriminants to detect calming and insight meditation in electroencephalographic (EEG) signals was assessed. The proposed methods were applied to EEG recordings from meditators practicing insight meditation and calming meditation b...

The hypothesis that the electrical activity of neural networks in the brain varies around the critical point is potentially important, as many simulations have proven that the efficiency of information processing should be highest at the critical point. Complexity of EEG signal using fractal dimension, entropy and complex noise characteristics was...

Background: Electrophysiological studies have demonstrated that the brain is active even in the absence of explicit input or output. Microstates represent subsequent coherent activation within the global functional brain networks. Continuous wavelet coherence is a measure of time-frequency changes in linear dependencies between EEG channels. Objec...